Deep learning practices in the agriculture sector can address many challenges faced by the
farmers such as disease detection, yield estimation, soil profile estimation, etc. In this paper …

Maydis leaf blight (MLB) of maize (Zea Mays L.), a serious fungal disease, is capable of
causing up to 70% damage to the crop under severe conditions. Severity of diseases is …

To ensure food security for the ever-growing population, agricultural production needs to be
increased by 50% by 2050 with the dwindling natural resources. Recently, crop yields are …

The field of computer science known as machine learning is used to create algorithms that
have the ability to self-learn or learn on their own. This is how the phrase" Machine …

To improve the wheat crop's yield, leaf disease detection has been considered as an
important research area. In the digital image processing field, computer vision and deep …

Artificial intelligence (AI) is the branch of science that deals with the development of
machines to mimic human intelligence. Machine learning (ML) is a subdomain of AI where …

Wheat, a crucial crop globally and a staple food for millions, faces numerous disease
threats, impacting yields and food security. However, wheat crops are vulnerable to many …

Computational models have been an important contributor to growth in agriculture. Artificial
Intelligence (AI) has revolutionized agriculture by efficiently disseminating information to …

Weed management is a critical aspect of modern agriculture, directly impacting crop yield
and quality. In rice cultivation, weeds can significantly reduce productivity, leading to …

Population Diversity, Pathogenomics and Development of Diagnostics of Emerging Fungal Plant
Pathogens-A Training Manual, TB-ICN: 310/2023 Page 2 Page 3 0 World Bank-ICAR funded …